As a young woman, I didn’t worry too much about bone health. But as I get a bit older, I’ve started to think about things like calcium supplementation and weight-bearing exercise as ways to avoid problems down the road. There’s not much I can do about my genes, though. Now a huge consortium of researchers, including Stanford’s John Ioannidis, MD, DSc, has identified 32 new genetic regions associated with osteoporosis and bone fracture. The research is published (subscription required) today in Nature Genetics. According to our release:
The unprecedented prospective meta-analysis – which involved 17 genome-wide association studies, 180 researchers and more than 100,000 participants – also identified six regions strongly correlated with the risk of fractures of the femur or lower back. However, the predictive power of the study for individuals is relatively low: Those with multiple risk-increasing variants are only about three to four times more likely than those with the fewest variants to have lower bone mineral density and experience fractures.
The results underscore the difficulty in identifying genetic culprits of complex diseases. That’s because, many times, there isn’t just one, or two, or even three. Instead, there are tens or hundreds, all of which probably interact with the environment to generate disease risk. But that doesn’t mean genetic insights are unimportant:
Although factors such as body weight, build and gender are currently much more predictive of osteoporosis than any of the genetic variants identified in the study, the research identified many pathways involved in bone health. The biological relevance of the findings was confirmed by the fact that some of the pathways are already targeted by current anti-osteoporosis drugs. Other, previously unsuspected pathways will help researchers understand more about the disease and how to develop drugs to fight it.
Finally, the research offers a glimpse into what is likely to be the future of “genome-wide association studies”, or GWAS, that strive to pinpoint associations between genes and various conditions. With so many genes involved, the number of participants (and researchers) necessary to draw statistically significant conclusions is increasing dramatically:
“The real power of our study lies in the ability to generate prospectively a huge combined data set and analyze it as a single study,” said Ioannidis. “It’s likely that our expectations have been too high in terms of what single studies can accomplish. Each one of the many teams identified at most only one or two markers; many found none.”
Instead, increasingly larger studies will be needed to identify genes important in disease. “In reality, there may be 500 or more gene variants regulating osteoporosis,” said Ioannidis. “To find all of them, we’ll need to study millions of patients. Is this unrealistic? I don’t think so. Sooner or later this will be feasible.”